Description: David E. Goldberg所写经典遗传算法源码，包含多种经典遗传算法，不可多得的学习资料。-David E. Goldberg, written in classical genetic algorithm source, covering a wide variety of classical genetic algorithm, a rare learning materials. Platform: |
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Author:颜晨阳 |
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Description: 采用纯C语言编写的遗传算法源程序，广泛用于数据挖掘和人工智能中-using pure C language source of the genetic algorithm, widely used in data mining and artificial intelligence! ! Platform: |
Size: 86158 |
Author:周君 |
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Description: 这是一个非常简单的遗传算法源代码，代码保证尽可能少，实际上也不必查错。对一特定的应用修正此代码，用户只需改变常数的定义并且定义“评价函数”即可。注意代码 的设计是求最大值，其中的目标函数只能取正值；且函数值和个体的适应值之间没有区别。该系统使用比率选择、精华模型、单点杂交和均匀变异。如果用 Gaussian变异替换均匀变异，可能得到更好的效果。代码没有任何图形，甚至也没有屏幕输出，主要是保证在平台之间的高可移植性。读者可以从ftp.uncc.edu, 目录 coe/evol中的文件prog.c中获得。要求输入的文件应该命名为‘gadata.txt’；系统产生的输出文件为‘galog.txt’。输入的 文件由几行组成：数目对应于变量数。且每一行提供次序——对应于变量的上下界。如第一行为第一个变量提供上下界，第二行为第二个变量提供上下界，等等。 -This is a very simple genetic algorithm source code, code guarantees minimal, in fact there is no need Checking. For a specific application to amend this code, users only need to change the constant definition and the definition of "evaluation function" can. Attention to the design of the code for the maximum, the objective function can only take positive; and function and adapt to the individual was no difference between the value. The system uses ratio choices, the essence model, single point of hybridization and mutation uniform. If Gaussian variation replacement uniform variation, may be a better result. Code no graphics, or even no screen output, mainly to ensure that the platforms to the high portability. Readers can get ftp.uncc.edu. Contents coe / evol prog.c the document Platform: |
Size: 3758 |
Author:nokia8 |
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Description: 这是一个非常简单的遗传算法源代码，代码保证尽可能少，实际上也不必查错。对一特定的应用修正此代码，用户只需改变常数的定义并且定义“评价函数”即可。注意代码 的设计是求最大值，其中的目标函数只能取正值；且函数值和个体的适应值之间没有区别。该系统使用比率选择、精华模型、单点杂交和均匀变异。如果用 Gaussian变异替换均匀变异，可能得到更好的效果。代码没有任何图形，甚至也没有屏幕输出，主要是保证在平台之间的高可移植性。读者可以从ftp.uncc.edu, 目录 coe/evol中的文件prog.c中获得。要求输入的文件应该命名为‘gadata.txt’；系统产生的输出文件为‘galog.txt’。输入的 文件由几行组成：数目对应于变量数。且每一行提供次序——对应于变量的上下界。如第一行为第一个变量提供上下界，第二行为第二个变量提供上下界，等等。 -This is a very simple genetic algorithm source code, code guarantees minimal, in fact there is no need Checking. For a specific application to amend this code, users only need to change the constant definition and the definition of "evaluation function" can. Attention to the design of the code for the maximum, the objective function can only take positive; and function and adapt to the individual was no difference between the value. The system uses ratio choices, the essence model, single point of hybridization and mutation uniform. If Gaussian variation replacement uniform variation, may be a better result. Code no graphics, or even no screen output, mainly to ensure that the platforms to the high portability. Readers can get ftp.uncc.edu. Contents coe/evol prog.c the document Platform: |
Size: 3072 |
Author: |
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Description: 01背包问题的C++源程序，写的比较简单-01 knapsack problem C++ Source code, written in relatively simple Platform: |
Size: 49152 |
Author:sandy chen |
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Description: 基于改进后的遗传算法 交叉、变异操作后，在windows平台下用C语言实现求解TSP问题-Based on the improved genetic algorithm crossover and mutation operation, in windows platform using C language for solving TSP problems Platform: |
Size: 3072 |
Author:lc |
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Description: 详细讲述模拟退火算法的理论原理。并TSP问题为例进行讲解，并各处多种语言的源代码，包括c，matlab以及delphi。
-Simulated annealing algorithm described in detail the theory of principle. And TSP as an example to explain the problem and the source code of various languages, including c, matlab, as well as delphi. Platform: |
Size: 25600 |
Author:lian |
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Description: 这是一个非常简单的遗传算法源代码，是由Denis Cormier (North Carolina State University)开发的，Sita S.Raghavan (University of North Carolina at Charlotte)修正。代码保证尽可能少，实际上也不必查错。对一特定的应用修正此代码，用户只需改变常数的定义并且定义“评价函数”即可。注意代码的设计是求最大值，其中的目标函数只能取正值；且函数值和个体的适应值之间没有区别。该系统使用比率选择、精华模型、单点杂交和均匀变异。如果用Gaussian变异替换均匀变异，可能得到更好的效果。代码没有任何图形，甚至也没有屏幕输出，主要是保证在平台之间的高可移植性。读者可以从ftp.uncc.edu,目录 coe/evol中的文件prog.c中获得。要求输入的文件应该命名为‘gadata.txt’；系统产生的输出文件为‘galog.txt’。输入的文件由几行组成：数目对应于变量数。且每一行提供次序——对应于变量的上下界。如第一行为第一个变量提供上下界，第二行为第二个变量提供上下界，等等。
-This is a very simple genetic algorithm source code, by Denis Cormier (North Carolina State University) developed, Sita S. Raghavan (University of North Carolina at Charlotte) as amended. Code to ensure that as little as possible, in fact, do not have errors. The application of a specific amendment to this code, the user can change the definition of constants and the definition of "evaluation function" can be. Note the code is designed for maximum value, in which the objective function can only take positive and function to adapt to individual values and there was no difference between values. The system uses the ratio of choice, the best model, a single point of hybridization and uniform mutation. If the variation of the replacement of uniform Gaussian mutation may be more effective. Code without any graphics, or even no screen output, mainly to ensure a high portability between platforms. Readers can ftp.uncc.edu, directory coe/evol documents obtained prog.c. Asked to enter the fi Platform: |
Size: 4096 |
Author:Kaavield |
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Description: 这是一个非常简单的遗传算法源代码，是由Denis Cormier (North Carolina State University)开发的，Sita S.Raghavan (University of North Carolina at Charlotte)修正。代码保证尽可能少，实际上也不必查错。对一特定的应用修正此代码，用户只需改变常数的定义并且定义“评价函数”即可。注意代码 的设计是求最大值，其中的目标函数只能取正值；且函数值和个体的适应值之间没有区别。该系统使用比率选择、精华模型、单点杂交和均匀变异。如果用 Gaussian变异替换均匀变异，可能得到更好的效果。代码没有任何图形，甚至也没有屏幕输出，主要是保证在平台之间的高可移植性。读者可以从ftp.uncc.edu, 目录 coe/evol中的文件prog.c中获得。要求输入的文件应该命名为‘gadata.txt’；系统产生的输出文件为‘galog.txt’。输入的 文件由几行组成：数目对应于变量数。且每一行提供次序——对应于变量的上下界。如第一行为第一个变量提供上下界，第二行为第二个变量提供上下界，等等。 -It is a very simple genetic algorithm source code, is Denis Cormier (North Carolina State University) developed, Sita S. Raghavan (University of North Carolina at Charlotte) amendment. Code to ensure as little as possible, in fact, do not have to troubleshooting. The application of a specific amendment to this code, the user simply changes the definition of constants and the definition of "evaluation function" can be. Note that the code is designed to seek maximum value, in which the objective function can only take positive and the function value and the individual is no difference between the fitness value. The system uses the rate selection, the essence of model, single-point crossover and uniform mutation. If you replace the uniform mutation with Gaussian mutation, may be more effective. Code without any graphic or even no screen output, mainly to ensure a high portability between platforms. Readers can ftp.uncc.edu, directory coe/evol file prog.c obtained. Required input file sho Platform: |
Size: 8192 |
Author:李礼 |
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Description: 用遗传算法解决VRP问题的C语言源代码，欢迎交流-VRP with a genetic algorithm to solve the problem of the C language source code, welcomed the exchange Platform: |
Size: 7168 |
Author:MGC |
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Description: 压缩包内收集了一些C#常用的7种遗传算法，这些算法主要是保存超个体的基本遗传算法、仿生双倍体遗传算法、人工双倍体遗传算法、保存历史最优解的遗传算法、保存历史最优解的仿生双倍体遗传算法等，另外，对随机数的产生机制进行了优化，在内层循环中也能产生高质量的随机数。部分功能可通过源码爱好者测试截图中看出-Compressed within a collection of some of the commonly used C# 7 kinds of genetic algorithms is mainly to save over the individual' s genetic algorithm, bionic diploid genetic algorithms, artificial diploid genetic algorithm, the optimal solution to save the history of the genetic algorithm, save history of the optimal solution bionic diploid genetic algorithms, etc. In addition, the random number generation mechanism is optimized in the inner loop can produce high-quality random numbers. Some features can be seen in source enthusiasts test shots. Platform: |
Size: 21504 |
Author:罗云峰 |
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Description: C语言编写的遗传算法源程序，程序框架好，易懂，适合初学真。-The genetic algorithm source code written in the C language, the program framework, easy to understand, suitable for beginner true. Platform: |
Size: 2048 |
Author:李平 |
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Description: 这是一个非常简单的遗传算法源代码，是由Denis Cormier (North Carolina State University)开发的，Sita S.Raghavan (University of North Carolina at Charlotte)修正。代码保证尽可能少，实际上也不必查错。对一特定的应用修正此代码，用户只需改变常数的定义并且定义“评价函数”即可。注意代码的设计是求最大值，其中的目标函数只能取正值；且函数值和个体的适应值之间没有区别。该系统使用比率选择、精华模型、单点杂交和均匀变异。如果用Gaussian变异替换均匀变异，可能得到更好的效果。代码没有任何图形，甚至也没有屏幕输出，主要是保证在平台之间的高可移植性。读者可以从ftp.uncc.edu,目录 coe/evol中的文件prog.c中获得。要求输入的文件应该命名为‘gadata.txt’；系统产生的输出文件为‘galog.txt’。输入的文件由几行组成：数目对应于变量数。且每一行提供次序——对应于变量的上下界。如第一行为第一个变量提供上下界，第二行为第二个变量提供上下界，等等。-This is a very simple genetic algorithm source code, by Denis Cormier (North Carolina State University) developed, Sita S.Raghavan (University of North Carolina at Charlotte) corrected. Code to ensure as little as possible, in fact, do not have to troubleshoot. For a specific application fix this code, users only need to change the definition of constants and the definition of "evaluation function" button. Note that the code is designed for the maximum, in which the objective function can only take positive values , and fitness function values and the individual is no difference between the values . The system uses the ratio selection, the essence of the model, a single point crossover and uniform mutation. If you replace the uniform mutation with Gaussian mutation may get better results. Code has no graphics, or even no screen output, mainly to ensure high portability between platforms. Readers can ftp.uncc.edu, catalog coe/evol files prog.c ge Platform: |
Size: 35840 |
Author:周成 |
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